Abstract
A distributed processing System is a collection of heterogeneous processors which requires systematic assignment of a set of “m” tasks T = {t1, t2….tm} of a program to a set of “n” processors P = {p1, p2….pn}, (where, m > > n) to achieve the efficient utilization of available processor’s capacity. If this step is not performed properly, an increase in the number of processors may actually result in a decrease in the total system throughput. The Inter-Task Communication (ITC) time is always the most costly and the least reliable factor in distributed processing environment. This paper deals a heuristic task allocation model which performs the proper allocation of task to most suitable processor to get an optimal solution. A fuzzy membership functions is developed for making the clusters of tasks with the constraints to maximize the throughput and minimize the parallel execution time of the system.
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Yadav, P.K., Pradhan, P., Singh, P.P. (2012). A Fuzzy Clustering Method to Minimize the Inter Task Communication Effect for Optimal Utilization of Processor’s Capacity in Distributed Real Time Systems. In: Deep, K., Nagar, A., Pant, M., Bansal, J. (eds) Proceedings of the International Conference on Soft Computing for Problem Solving (SocProS 2011) December 20-22, 2011. Advances in Intelligent and Soft Computing, vol 130. Springer, India. https://doi.org/10.1007/978-81-322-0487-9_16
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DOI: https://doi.org/10.1007/978-81-322-0487-9_16
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